Generative adversarial networks (GANs) have recently become a hot research topic;
however, they have been studied since 2014, and a large number of algorithms have been …

Speaker identity is one of the important characteristics of human speech. In voice
conversion, we change the speaker identity from one to another, while keeping the linguistic …

We propose a method for editing images from human instructions: given an input image and
a written instruction that tells the model what to do, our model follows these instructions to …

Recent text-to-image diffusion models are able to generate convincing results of
unprecedented quality. However, it is nearly impossible to control the shapes of different …

This paper develops a unified framework for image-to-image translation based on
conditional diffusion models and evaluates this framework on four challenging image-to …

Denoising diffusion probabilistic models (DDPM) have shown remarkable performance in
unconditional image generation. However, due to the stochasticity of the generative process …

GAN inversion aims to invert a given image back into the latent space of a pretrained GAN
model so that the image can be faithfully reconstructed from the inverted code by the …

In image-to-image translation, each patch in the output should reflect the content of the
corresponding patch in the input, independent of domain. We propose a straightforward …

We propose a neural talking-head video synthesis model and demonstrate its application to
video conferencing. Our model learns to synthesize a talking-head video using a source …

Metrics for evaluating generative models aim to measure the discrepancy between real and
generated images. The oftenused Frechet Inception Distance (FID) metric, for example …